@pluginagentmarketplace/machine-learning
Python machine learning with scikit-learn, PyTorch, and TensorFlow
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SKILL.md
| name | Machine Learning |
| description | Python machine learning with scikit-learn, PyTorch, and TensorFlow |
| version | 2.1.0 |
| sasmp_version | 1.3.0 |
| bonded_agent | 03-data-science |
| bond_type | PRIMARY_BOND |
| retry_strategy | exponential_backoff |
Python Machine Learning Skill
Overview
Build machine learning models using Python libraries including scikit-learn, PyTorch, and supporting tools.
Topics Covered
Scikit-learn
- Data preprocessing
- Model selection
- Training pipelines
- Cross-validation
- Hyperparameter tuning
PyTorch Basics
- Tensor operations
- Neural network modules
- Training loops
- DataLoader usage
- GPU acceleration
Feature Engineering
- Feature selection
- Dimensionality reduction
- Feature scaling
- Encoding techniques
- Missing data handling
Model Evaluation
- Metrics selection
- Confusion matrix
- ROC curves
- Learning curves
- Model comparison
MLOps Basics
- Model serialization
- Experiment tracking (MLflow)
- Model versioning
- Serving models
- Reproducibility
Prerequisites
- Python fundamentals
- NumPy and Pandas
- Statistics basics
Learning Outcomes
- Train ML models
- Evaluate model performance
- Build ML pipelines
- Deploy models to production
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Bill of Materials
Everything this skill can do — files, network, commands, and more.
No demos yet. To add one, ask your AI agent: "Submit a demo for @pluginagentmarketplace/machine-learning" — or upload via the API.
To add a demo, ask your AI agent: "Submit a demo for @pluginagentmarketplace/machine-learning"
No eval data yet. Eval results are published via the SkillSafe API.